Quo Vadis, Indoor Location?

Today, the majority of 911 (emergency) calls are made from cellphones, making it necessary to pinpoint indoor location, including floor level, with reasonable accuracy.

During one of my shopping jaunts to the mall, my school buddy declared that we're close to the day when we will be able to navigate within large indoor spaces, single or multi-level, with full 3D maps. My first thought? What kind of technology driver is needed for this to happen?

The concept of indoor location navigation is not new, but the current impetus is coming from an unlikely source, E-911. Apparently, the FCC conceived of E-911 wireless rules when access to cellphones was minimal and most 911 calls were from landlines. Today the majority of calls for help are from cellphones, making it necessary to pinpoint indoor location, including floor level, with reasonable accuracy. Current accuracy stands at around 100-300 m -- equal to a city block -- making things difficult for first responders. However, it looks like indoor location accuracy and requirements will be characterized separately from outdoor. The proposed accuracy requirements stand at 50 m for horizontal coordinates and 3 m for vertical coordinates.

So, what more is needed from GPS and cellphones to make all this happen? GPS, as we all know and have experienced, works best outdoors. Why? Well, GPS uses weak signals and needs a minimum of 3-4 satellites to narrow down the position. Can WiFi or Bluetooth beacons, which are common indoors and deliver higher accuracy, help here? I think they can. Some companies (e.g., iBeacon and Skyhook Wireless) have developed services around this. Can public safety ride on these technologies? Not in the near future -- the range of these beacons is smaller, and you need more beacons to cover a wide area, which means a user would need a network management operator on a nationwide scale to certify the beacon location and guarantee quality of service.

This was evident from the three companies -- Qualcomm, Polaris Wireless, and NextNav -- that took part in the evaluation process conducted by CSRIC, the committee tasked by the FCC to evaluate currently available indoor location technologies. Two of the three companies already deal with network management. The test methodology included calls placed everywhere from dense urban to rural areas and from building structures made of different materials. Among the parameters measured were accuracy in x-y-z coordinates and time taken to first fix location. Only NextNav volunteered for the z-axis coordinates. The others felt that providing raw height might not be useful until annotated on to 3D models of building structures.

Qualcomm, true to its CDMA origins, showcased its Advanced Forward Link Trilateration (AFLT) technology. In AFLT, weak GPS signals from three satellites are substituted with strong signals from any three CDMA towers whose positions are known. Since CDMA signals are synchronized to a common time base (as is the case with GPS), your position is calculated based on the time differences in the signals' arrival. The pros: Handsets require only software/firmware modification, and signal strengths are higher. The cons: Having three base stations in sufficient proximity to aid in trilateration can be challenging in dense urban areas.

Polaris Wireless technology is quite unique and innovative. Just as every human has unique fingerprints for identification, Polaris Wireless has a database of locations tagged against RF imprint, based on signal strength and interference patterns. During a call, your cellphone transmits the necessary RF parameters as measured on location to a server that runs it against the tagged locations for a match. It would be interesting to see what kind of location accuracy one can obtain using this technology, since it is directly related to how extensive, granular, and recent the RF signature scan is.

On the face of it, NextNav's technology -- which is based on a terrestrial network and signal arrival time -- looks very similar to AFLT, but there are some significant differences. Cellular tower placement/position is decided with the goal of increasing coverage and addressing cell traffic, but rarely for location. So NextNav's secret sauce is in the optimal or strategic placement of terrestrial towers to aid in the trilateration process. The result? Better accuracy. NextNav's other differentiator is in detecting height from barometric readings taken at the tower and receiver. This is an ingenious innovation, since air pressure is a localized phenomenon. So the pros are very little modification to cellphones and greater location accuracy with regard to vertical coordinates. The main con is the installation of new towers.

Horizontal location accuracy in meters.
(Image: CSRIC WG3 report)

So how do these companies and technologies fare among themselves? I expected NextNav and Qualcomm AFLT technology to perform similarly, due to their terrestrial beacon and arrival time-based technology. But results for dense urban and urban area show that NextNav performed better than AFLT. Does this mean that strategic beacon placement coupled with a different signal structure (unlike CDMA) holds the key for better location fix?

It is too early to declare winners at this time. This round of evaluation showed that current participants have come close but are still shy of the FCC search rings. There is an expectation that forthcoming evaluations may have new players like Boeing (using Iridium satellites), while current participants will improve and showcase their next-generation technologies to hit the mark.

I feel horizontal location and accuracy improvements are relatively easy compared to fixing vertical location and accuracy. It will be interesting to see what future evaluations show us. Those that meet the requirements will not find instant gold; market dynamics with cellular network operators will determine who gets the backing. Remember that some of these technologies have upfront costs, take time to deploy, and may involve handset modification.

I feel an overriding and important aspect will be how scalable the technology is, so that gradual improvements increase accuracy over time without the need to rip things out over and over again. Until then, keep watching and say, "Quo vadis, indoor location?"

The real key is going to be figuring out how to prevent the kind of correlation that I describe. I am not sure it can be done. We may well have to accept the loss of privacy as a side consequence of the benefits.

But then, privacy is a cultural concept anyway. People who deal with shared living spaces, such as a six-person family in a two-bedroom house, have a different expecation of privacy than those who have one-person spaces.

It's also a matter of trust. Private simply means information that you want to be able to control access to, and you might be willing to share that information with those you trust not to use it to harm you or more widely if you trust that the information cannot be used in any way to harm you.

@RichQ: Oddly, perhaps, I don't mind anyone knowing those movement pattern, as long as they cannot be connected directly to me.

As always, you hit the nail on the head. I totally agree with this -- I think the whole concept of "Big Data" is tremendously exciting when applied to the way in which people do "stuff," but I prefer it to be used as a generalization of lots of people and not to focus on individuals.

It seems to me that the key to privacy is to disconnect location information from the identity. If I place a 911 call, of course, I will want to be sure that the location information is linked to the call details (such as stating the nature of the medical emergency). But otherwise, I would prefer that no one is able to determine where I am and infer what I am doing based on my movement patterns.

Oddly, perhaps, I don't mind anyone knowing those movement pattern, as long as they cannot be connected directly to me. I can see great benefit to folks like highway planners, for instance, knowing when and how the commuters get from their homes to their offices. That, to me, does not violate privacy. But being able to extract the endpoint addresses of a given movement, and correlate that with a name, is a violation of privacy.

This presents a problem because there are other information sources that can be correlated with the data to "fill in the gaps" of such an association. Simply knowing where movement starts and stops, if correlated with housing and employment records, would be enough to determine with fair accuracy who the movement record is about. So, it's not enough to simply separate the identity from the data.

@Edward: How does this added locating functionality affect our chnaging sense of privacy?

I think the key point is when you say "our changing sense of privacy" -- things certainly are changing.

If you were to go back say 100 years ago -- you could "pick up sticks" and move to a new town and create a new identity.... on the other hand, when you did move to a new place people tended to be inquisitive -- and a lot of ladies stayed at home and looked out of windows -- pretty much everyone in a small town knew what everyone else was doing.

These days people tend to leave you alone and they aren't so nosy -- but your likes/dislikes etc. can be tracked via online means.

This is a really complicated area -- there are lots of advantages to having your information out there -- but lots of disadvantages also.

In the case of a 911 call, it would make sense to me that even if you've set your cell phone to be in "stealth mode" -- not reporting your location or whatever, if you make a 911 call, that overrides the privicy settings...

Good point, Max. More apps give us better locating functionality. Now to inject a (perhaps) not directly relevant point: How does this added locating functionality affect our chnaging sense of privacy?

There's also the fact that things like smartphones are becoming increasingly stuffed with sensors (magnetometers, gyros, accelerometers....) coupled with the computational processing (in software and hardware) to make them context aware so they knwo if you are sitting, leaning against a wall, going up/down in/on an elevator/escalator ... so they can add this info into the location-determining mix...